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定量分析突触间蛋白质排列:单分子定位显微镜数据分析案例。

Quantification of trans-synaptic protein alignment: A data analysis case for single-molecule localization microscopy.

机构信息

CAS Key Laboratory of Brain Function and Disease and Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China.

Program in Neuroscience and Department of Physiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA.

出版信息

Methods. 2020 Mar 1;174:72-80. doi: 10.1016/j.ymeth.2019.07.016. Epub 2019 Jul 17.

Abstract

Nanoscale distribution of proteins and their relative positioning within a defined subcellular region are key to their physiological functions. Thanks to the super-resolution imaging methods, especially single-molecule localization microscopy (SMLM), mapping the three-dimensional distribution of multiple proteins has been easier and more efficient than ever. Nevertheless, in spite of the many tools available for efficient localization detection and image rendering, it has been a challenge to quantitatively analyze the 3D distribution and relative positioning of proteins in these SMLM data. Here, using heterogeneously distributed synaptic proteins as examples, we describe in detail a series of analytical methods including detection of nanoscale density clusters, quantification of the trans-synaptic alignment between these protein densities, and automatic en face projection and averaging. These analyses were performed within customized Matlab routines and we make the full scripts available. The concepts behind these analytical methods and the scripts can be adapted for quantitative analysis of spatial organization of other macromolecular complexes.

摘要

蛋白质在特定亚细胞区域内的纳米级分布及其相对位置对于其生理功能至关重要。得益于超分辨率成像方法,尤其是单分子定位显微镜(SMLM),现在比以往任何时候都更容易且更高效地绘制多个蛋白质的三维分布。然而,尽管有许多工具可用于高效的定位检测和图像渲染,但定量分析这些 SMLM 数据中蛋白质的 3D 分布和相对位置仍然是一个挑战。在这里,我们以异质分布的突触蛋白为例,详细描述了一系列分析方法,包括纳米级密度团簇的检测、这些蛋白密度之间的跨突触对准的量化,以及自动的共面投影和平均化。这些分析是在定制的 Matlab 例程中进行的,我们提供了完整的脚本。这些分析方法背后的概念和脚本可以适用于其他大分子复合物的空间组织的定量分析。

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